ROC analysis in patient specific quality assurance.

PURPOSE This work investigates the use of receiver operating characteristic (ROC) methods in patient specific IMRT quality assurance (QA) in order to determine unbiased methods to set threshold criteria for γ-distance to agreement measurements. METHODS A group of 17 prostate plans was delivered as planned while a second group of 17 prostate plans was modified with the introduction of random multileaf collimator (MLC) position errors that are normally distributed with σ ≈ ± 0.5, ± 1.0, ± 2.0, and ± 3.0 mm (a total of 68 modified plans were created). All plans were evaluated using five different γ-criteria. ROC methodology was applied by quantifying the fraction of modified plans reported as "fail" and unmodified plans reported as "pass." RESULTS γ-based criteria were able to attain nearly 100% sensitivity/specificity in the detection of large random errors (σ > 3 mm). Sensitivity and specificity decrease rapidly for all γ-criteria as the size of error to be detected decreases below 2 mm. Predictive power is null with all criteria used in the detection of small MLC errors (σ < 0.5 mm). Optimal threshold values were established by determining which criteria maximized sensitivity and specificity. For 3%/3 mm γ-criteria, optimal threshold values range from 92% to 99%, whereas for 2%/2 mm, the range was from 77% to 94%. CONCLUSIONS The optimal threshold values that were determined represent a maximized test sensitivity and specificity and are not subject to any user bias. When applied to the datasets that we studied, our results suggest the use of patient specific QA as a safety tool that can effectively prevent large errors (e.g., σ > 3 mm) as opposed to a tool to improve the quality of IMRT delivery.

[1]  M. Oldham,et al.  Evaluation of a 2D diode array for IMRT quality assurance. , 2004, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[2]  J Eduardo Villarreal-Barajas,et al.  On the use of the MLC dosimetric leaf gap as a quality control tool for accurate dynamic IMRT delivery. , 2011, Medical physics.

[3]  Todd Pawlicki,et al.  Process control analysis of IMRT QA: implications for clinical trials , 2008, Physics in medicine and biology.

[4]  Michael B Sharpe,et al.  Statistical process control for IMRT dosimetric verification. , 2008, Medical physics.

[5]  P. Metcalfe,et al.  Verification of a rounded leaf-end MLC model used in a radiotherapy treatment planning system , 2006, Physics in medicine and biology.

[6]  Jatinder R Palta,et al.  Quality assurance of intensity-modulated radiation therapy. , 2008, International journal of radiation oncology, biology, physics.

[7]  K Krishnamurthy,et al.  Formulation and initial experience on patient specific quality assurance for clinical implementation of dynamic IMRT. , 2009, The Gulf journal of oncology.

[8]  P. Jursinic,et al.  A 2-D diode array and analysis software for verification of intensity modulated radiation therapy delivery. , 2003, Medical physics.

[9]  Lucila Ohno-Machado,et al.  The use of receiver operating characteristic curves in biomedical informatics , 2005, J. Biomed. Informatics.

[10]  Alejandra Rangel,et al.  Tolerances on MLC leaf position accuracy for IMRT delivery with a dynamic MLC. , 2009, Medical physics.

[11]  T. Pawlicki,et al.  Biological consequences of MLC calibration errors in IMRT delivery and QA. , 2012, Medical physics.

[12]  W. Jason Owen,et al.  Statistical Data Analysis , 2000, Technometrics.

[13]  Guanghua Yan,et al.  On the sensitivity of patient‐specific IMRT QA to MLC positioning errors , 2009, Journal of applied clinical medical physics.

[14]  Alejandra Rangel,et al.  The sensitivity of patient specific IMRT QC to systematic MLC leaf bank offset errors. , 2010, Medical physics.

[15]  D. Low,et al.  A technique for the quantitative evaluation of dose distributions. , 1998, Medical physics.

[16]  J. Palta,et al.  Dose variations with varying calculation grid size in head and neck IMRT , 2006, Physics in medicine and biology.

[17]  J. Radich,et al.  Comprehensive evaluation of time‐to‐response parameter as a predictor of treatment failure following imatinib therapy in chronic phase chronic myeloid leukemia: Which parameter at which time‐point does matter? , 2010, American journal of hematology.

[18]  Benjamin E Nelms,et al.  Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors. , 2011, Medical physics.

[19]  C. Ling,et al.  Physical and dosimetric aspects of a multileaf collimation system used in the dynamic mode for implementing intensity modulated radiotherapy. , 1998, Medical physics.

[20]  Receiver Operating Characteristic Analysis in Medical Imaging , 2008 .

[21]  D. Tatsumi,et al.  Direct impact analysis of multi-leaf collimator leaf position errors on dose distributions in volumetric modulated arc therapy: a pass rate calculation between measured planar doses with and without the position errors , 2011, Physics in medicine and biology.

[22]  Parminder S Basran,et al.  An analysis of tolerance levels in IMRT quality assurance procedures. , 2008, Medical physics.

[23]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[24]  Gary A. Ezzell,et al.  The overshoot phenomenon in step‐and‐shoot IMRT delivery , 2001, Journal of applied clinical medical physics.

[25]  Todd Pawlicki,et al.  Moving from IMRT QA measurements toward independent computer calculations using control charts. , 2008, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[26]  J. Mechalakos,et al.  IMRT commissioning: multiple institution planning and dosimetry comparisons, a report from AAPM Task Group 119. , 2009, Medical physics.

[27]  Benjamin E Nelms,et al.  Moving from gamma passing rates to patient DVH-based QA metrics in pretreatment dose QA. , 2011, Medical physics.

[28]  Carrie R. H. Innes,et al.  Comparison of a linear and a non-linear model for using sensory-motor, cognitive, personality, and demographic data to predict driving ability in healthy older adults. , 2010, Accident; analysis and prevention.

[29]  Eric Aliotta,et al.  RapidArc patient specific mechanical delivery accuracy under extreme mechanical limits using linac log files. , 2012, Medical physics.

[30]  A. Verma,et al.  Evaluation of diffusion-weighted imaging as a predictive marker for tumor response in patients undergoing chemoradiation for postoperative recurrences of cervical cancer. , 2012, Journal of cancer research and therapeutics.

[31]  J. Hanley,et al.  A method of comparing the areas under receiver operating characteristic curves derived from the same cases. , 1983, Radiology.

[32]  C. Hoggart,et al.  A risk model for lung cancer incidence. , 2012, Cancer prevention research.

[33]  K. Bush,et al.  Clinical significance of multi-leaf collimator positional errors for volumetric modulated arc therapy. , 2010, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.